Cluster analsyis of NERRS SWMP water quality national dataset (station medians)
For Questions, Dave Parrish (parrishd@vims.edu)
2025-05-22
NERR Cluster
nerr_h_comp<-read.csv('data/WQ-NUT_overallMedians.csv')
head(nerr_h_comp)## X station Station.Name Reserve.Code Reserve.Name State
## 1 1 acebb Big Bay ACE Ashepoo Combahee Edisto Basin SC
## 2 2 aceei Edisto Island ACE Ashepoo Combahee Edisto Basin SC
## 3 3 acefc Fishing Creek ACE Ashepoo Combahee Edisto Basin SC
## 4 4 acemc Mosquito Creek ACE Ashepoo Combahee Edisto Basin SC
## 5 5 acesp St. Pierre ACE Ashepoo Combahee Edisto Basin SC
## 6 6 apacp Cat Point APA Apalachicola Bay FL
## Latitude Longitude yr_start_wq yr_end_wq yr_start_nut yr_end_nut temp_median
## 1 32.49410 80.32410 2002 2015 2002 2014 21.90
## 2 32.50400 80.32470 2015 2022 2015 2022 22.05
## 3 32.63593 80.36556 2002 2022 2002 2022 21.25
## 4 32.55580 80.43800 2002 2022 2002 2022 21.60
## 5 32.52800 80.36144 2002 2022 2002 2022 21.90
## 6 29.70210 84.88020 2002 2022 2002 2022 23.75
## spcond_median sal_median do_mgl_median do_pct_median ph_median turb_median
## 1 47.7800 31.10 6.2 84.525 7.8 19
## 2 44.7400 28.90 6.1 80.700 7.7 17
## 3 11.1025 6.30 5.3 63.900 6.9 28
## 4 28.3100 17.40 5.9 73.300 7.4 24
## 5 45.1475 29.25 6.0 81.150 7.7 17
## 6 35.3100 22.30 7.0 93.525 8.0 8
## temp_nPoints spcond_nPoints sal_nPoints do_mgl_nPoints do_pct_nPoints
## 1 342706 324398 324398 280781 296626
## 2 272515 260624 260624 271318 272419
## 3 612647 601919 601919 560211 560214
## 4 589475 579229 579229 533877 534111
## 5 601172 586247 586256 543518 546812
## 6 599913 556305 556305 546218 546199
## ph_nPoints turb_nPoints temp_nMonths spcond_nMonths sal_nMonths
## 1 307775 345100 156 152 152
## 2 249262 247825 96 95 95
## 3 537181 563414 240 240 240
## 4 518378 553330 240 235 235
## 5 513352 574413 250 248 248
## 6 516729 556902 248 245 245
## do_mgl_nMonths do_pct_nMonths ph_nMonths turb_nMonths chla_nMonths
## 1 145 150 146 155 145
## 2 96 96 94 94 78
## 3 235 235 229 235 220
## 4 233 233 226 237 222
## 5 239 239 233 247 225
## 6 246 246 240 246 226
## nh4f_nMonths no23_nMonths po4f_nMonths chla nh4f no23f po4f
## 1 155 153 152 4.66300 0.047450 0.01525000 0.043125
## 2 78 72 82 6.82000 0.024425 0.02487500 0.025625
## 3 237 223 232 8.07750 0.051500 0.03945000 0.071600
## 4 234 226 232 7.53175 0.043575 0.03550000 0.053975
## 5 236 223 235 4.03400 0.052175 0.01675000 0.038500
## 6 226 224 225 6.15000 0.023500 0.04316667 0.002000colnames(nerr_h_comp)## [1] "X" "station" "Station.Name" "Reserve.Code"
## [5] "Reserve.Name" "State" "Latitude" "Longitude"
## [9] "yr_start_wq" "yr_end_wq" "yr_start_nut" "yr_end_nut"
## [13] "temp_median" "spcond_median" "sal_median" "do_mgl_median"
## [17] "do_pct_median" "ph_median" "turb_median" "temp_nPoints"
## [21] "spcond_nPoints" "sal_nPoints" "do_mgl_nPoints" "do_pct_nPoints"
## [25] "ph_nPoints" "turb_nPoints" "temp_nMonths" "spcond_nMonths"
## [29] "sal_nMonths" "do_mgl_nMonths" "do_pct_nMonths" "ph_nMonths"
## [33] "turb_nMonths" "chla_nMonths" "nh4f_nMonths" "no23_nMonths"
## [37] "po4f_nMonths" "chla" "nh4f" "no23f"
## [41] "po4f"nerr_h_comp$L10_turb <- log10(nerr_h_comp$turb_median)
nerr_h_comp$L10_po4f <- log10(nerr_h_comp$po4f)
nerr_h_comp$L10_no23f <- log10(nerr_h_comp$no23f)
nerr_h_comp$L10_nh4f <- log10(nerr_h_comp$nh4f)
nerr_h_comp$L10_chla <- log10(nerr_h_comp$chla)
nerr_h_comp <- nerr_h_comp %>%
dplyr::select(station,spcond_median, temp_median, do_mgl_median, ph_median, L10_turb, L10_chla, L10_nh4f, L10_no23f,L10_po4f)
nerr_h_comp <- nerr_h_comp %>%
rename(code = 'station',Temp='temp_median',SpCond='spcond_median',Turb='L10_turb',DO='do_mgl_median',NO23='L10_no23f',
NH4='L10_nh4f',PO4='L10_po4f',Chla='L10_chla',pH=ph_median)
colnames(nerr_h_comp)## [1] "code" "SpCond" "Temp" "DO" "pH" "Turb" "Chla" "NH4"
## [9] "NO23" "PO4"pca_nerr = prcomp(nerr_h_comp[,2:ncol(nerr_h_comp)], center = TRUE, scale = TRUE)
pca_nerr## Standard deviations (1, .., p=9):
## [1] 1.7068909 1.5262369 1.2014663 0.9311692 0.7962843 0.6342399 0.4307805
## [8] 0.3660578 0.3010445
##
## Rotation (n x k) = (9 x 9):
## PC1 PC2 PC3 PC4 PC5
## SpCond -0.47585553 -0.10562380 -0.369142363 -0.141788252 -0.1013437331
## Temp -0.14102731 -0.57419888 0.232807536 -0.002267199 -0.1173393145
## DO 0.07171512 0.57662754 0.180686050 -0.324798789 -0.0164644283
## pH -0.40576069 0.08797909 -0.138698800 -0.619283992 -0.2341459091
## Turb 0.43548332 -0.32300071 -0.008433355 -0.216721723 0.2498698202
## Chla 0.29325701 -0.32421987 0.109959369 -0.639363999 0.0005773586
## NH4 0.30422790 -0.13142462 -0.469706271 0.137706574 -0.7199640464
## NO23 0.45082453 0.30293329 -0.037769522 -0.106625058 -0.2392896835
## PO4 0.11155828 0.02026380 -0.723489502 -0.069263298 0.5318105938
## PC6 PC7 PC8 PC9
## SpCond -0.24626090 0.01484365 0.69135209 -0.23860450
## Temp 0.31736983 0.11528470 -0.19409288 -0.65631374
## DO -0.17543755 -0.38813613 -0.08889209 -0.57845920
## pH 0.47681893 -0.07602463 -0.22961813 0.29014323
## Turb 0.31688328 -0.58116855 0.39028419 0.07782562
## Chla -0.53367196 0.29780324 -0.08817841 0.08207387
## NH4 -0.13910680 -0.26781135 -0.19794148 -0.04453308
## NO23 0.41239471 0.55782809 0.36513120 -0.14272809
## PO4 0.07652751 0.14394777 -0.30188600 -0.24160832pca_nerr$rotation## PC1 PC2 PC3 PC4 PC5
## SpCond -0.47585553 -0.10562380 -0.369142363 -0.141788252 -0.1013437331
## Temp -0.14102731 -0.57419888 0.232807536 -0.002267199 -0.1173393145
## DO 0.07171512 0.57662754 0.180686050 -0.324798789 -0.0164644283
## pH -0.40576069 0.08797909 -0.138698800 -0.619283992 -0.2341459091
## Turb 0.43548332 -0.32300071 -0.008433355 -0.216721723 0.2498698202
## Chla 0.29325701 -0.32421987 0.109959369 -0.639363999 0.0005773586
## NH4 0.30422790 -0.13142462 -0.469706271 0.137706574 -0.7199640464
## NO23 0.45082453 0.30293329 -0.037769522 -0.106625058 -0.2392896835
## PO4 0.11155828 0.02026380 -0.723489502 -0.069263298 0.5318105938
## PC6 PC7 PC8 PC9
## SpCond -0.24626090 0.01484365 0.69135209 -0.23860450
## Temp 0.31736983 0.11528470 -0.19409288 -0.65631374
## DO -0.17543755 -0.38813613 -0.08889209 -0.57845920
## pH 0.47681893 -0.07602463 -0.22961813 0.29014323
## Turb 0.31688328 -0.58116855 0.39028419 0.07782562
## Chla -0.53367196 0.29780324 -0.08817841 0.08207387
## NH4 -0.13910680 -0.26781135 -0.19794148 -0.04453308
## NO23 0.41239471 0.55782809 0.36513120 -0.14272809
## PO4 0.07652751 0.14394777 -0.30188600 -0.24160832pca_nerr$x## PC1 PC2 PC3 PC4 PC5
## [1,] -0.200402235 -1.3716284766 -1.156218215 -0.319546336 0.218042300
## [2,] -0.101213563 -1.3688465409 -0.407624370 -0.435015947 0.474825539
## [3,] 2.251106345 -1.8307450578 -0.576056899 1.093229014 1.122228614
## [4,] 1.130268086 -1.5347449068 -0.749682819 0.097642905 0.688009239
## [5,] -0.090838185 -1.3742605387 -1.092429822 0.042622516 0.136904731
## [6,] -0.668846285 -0.7542562318 1.336204721 -0.719092436 -1.032696555
## [7,] -0.633027479 -0.7532834813 1.675570901 -1.053931619 -0.570004705
## [8,] 0.587244930 -1.3408750890 1.893257460 -0.420240900 -0.659889430
## [9,] 0.456143686 -1.2600239113 2.019446114 -0.066713981 -0.568200924
## [10,] -1.556844449 -0.8599200287 1.565632267 -0.822383041 -0.275651020
## [11,] 2.231707491 0.9245124975 -0.322147025 0.847785325 0.380157846
## [12,] 0.993945443 0.4138394685 1.277215629 0.385101977 1.657726094
## [13,] 2.996807469 -0.4093413434 0.620555242 1.530779719 0.532089229
## [14,] 2.578889729 -0.0126943829 1.720134459 -1.638732511 -0.643327845
## [15,] 2.972013063 0.4733720203 0.427812743 0.211414585 0.056120173
## [16,] 0.202135191 -0.1437396170 0.299160519 -0.861173464 0.103111402
## [17,] -1.317250949 0.6364755584 0.559372478 -0.820208903 -0.499045491
## [18,] 2.504200708 -0.0420175524 0.668102102 0.396502786 0.749849857
## [19,] 2.650104405 0.0333424818 0.418241010 0.299140842 0.611537175
## [20,] 1.779428554 -0.6287036473 -0.230970450 -0.689960289 0.572103437
## [21,] 3.500890689 -0.2477542409 0.757957832 -0.601802078 0.432152438
## [22,] 3.191791717 0.0782592771 0.685929154 0.078244142 -0.006123801
## [23,] 3.763380186 -0.0760233949 -0.058890355 -0.158826102 -0.172941476
## [24,] 3.280975587 -0.4972977652 -1.043869017 0.148998216 -0.169150158
## [25,] -0.682143036 -0.3024112143 -1.779002581 -0.112699864 -0.125511431
## [26,] -0.442781406 -0.3122467814 -1.715660920 -0.768751512 -0.602418359
## [27,] -0.361898273 0.2507669022 -1.672341817 -0.425375281 -0.531479672
## [28,] -0.469112447 1.2469059008 -1.548993174 -0.348276211 -0.638444749
## [29,] -0.403608782 -1.4954651152 1.565020771 0.488041905 0.702323319
## [30,] 0.008793802 -2.4950773359 0.743109306 1.863872253 0.066027246
## [31,] -1.084534932 -0.9989652274 1.734490439 -0.465565086 1.035095218
## [32,] -1.473759318 -0.8508444123 1.599950598 -1.280485174 0.811326546
## [33,] -0.450560532 1.1217288344 -0.372265258 -0.712758740 -0.029546294
## [34,] 0.668614015 1.1084910135 0.523134638 0.920650583 -0.353576626
## [35,] 0.570130570 0.5241760111 -0.974704554 -0.311168462 -0.195713944
## [36,] 1.239618709 0.2009062917 -1.255586508 -0.407288408 -0.754204112
## [37,] -1.444502463 -1.1671233889 -0.372951792 -0.252464884 -0.349625437
## [38,] 0.113926855 -1.9020131198 -0.180164217 0.598238574 0.588820774
## [39,] -0.446348680 -1.6793025968 -0.469757162 0.265813800 0.088469670
## [40,] -0.995893112 -1.3872279768 -0.483224963 -0.240095207 -0.281683631
## [41,] -3.027964976 -0.2234141996 0.721362143 0.801235308 -0.633435456
## [42,] -3.835626745 -0.0137166576 1.624765921 0.697734421 0.794234857
## [43,] -0.158808712 -2.6395082069 1.088743734 3.418297230 1.917929516
## [44,] 1.977975795 2.1824657315 -0.103368017 -0.210896570 0.337608506
## [45,] 0.592960851 2.2460243461 -0.145075515 0.415554334 -0.071304835
## [46,] -0.311428188 3.2497037510 1.471969521 -0.287988139 -0.461674468
## [47,] 1.620985986 1.1036946924 0.826206821 0.280418832 -0.198529765
## [48,] 1.373952902 1.3364978751 0.848868152 0.160140710 -0.184280539
## [49,] -1.093629908 0.3834892787 -0.291625481 -0.974116310 0.744920454
## [50,] -0.969655799 0.2534052668 -0.190459330 -0.807629787 0.729378247
## [51,] 2.327756907 0.8003908611 1.879419408 2.266133651 1.188670257
## [52,] 0.773992992 0.8162425813 0.006019797 0.479491312 0.081344354
## [53,] -2.225347032 -2.4733204839 0.154754492 1.223835897 -1.511682740
## [54,] -2.783970485 -1.5595089404 0.735263984 1.555247813 -2.261474309
## [55,] -3.589013613 -0.7308212872 0.932792928 1.447992394 -2.114486266
## [56,] -3.377015091 -0.7617413519 0.693250289 1.705113946 -1.966007942
## [57,] -1.098870382 3.5338504324 -1.081945910 -0.130526372 0.062650001
## [58,] -1.068722248 3.4291910363 -0.497705539 -0.829821368 0.275441956
## [59,] -1.432547065 3.6603403021 -0.898474939 -0.110579070 0.025737292
## [60,] -1.293086085 3.7749664712 -0.804811104 -0.360103220 -0.079252269
## [61,] 1.820782933 1.1043111257 1.015708140 -0.636520991 -0.663248537
## [62,] 1.716814118 1.0308810119 0.411319244 -0.137532040 -1.434833366
## [63,] 0.687219935 0.9388947705 1.453922063 -0.119340969 -0.075809400
## [64,] 1.738179687 -0.8672086429 0.545401703 0.369344054 1.213091293
## [65,] -2.047181955 -0.8432391422 0.849468340 -1.376572855 1.507255639
## [66,] -1.491216160 -0.9825672954 0.457046271 -1.268093769 1.789807668
## [67,] -1.210164987 -0.9596908541 0.662321087 -1.439722041 2.219623981
## [68,] -1.641186601 -1.0075826426 0.849343395 -1.597527957 1.887088237
## [69,] -2.360956882 -0.8693036050 1.141307019 -0.985282761 0.843374489
## [70,] -1.547947533 0.5694738280 -0.594717247 1.162334194 0.664706741
## [71,] -2.054506895 1.8437973242 -0.421696017 -0.029493929 0.454390342
## [72,] -2.450808989 1.9074444487 -0.350663902 0.033744764 0.480026709
## [73,] -2.615856736 1.8977266476 -0.061879094 0.015686479 0.720067705
## [74,] -0.698045232 -1.2542467284 -0.554445303 0.039682384 -0.326488311
## [75,] -0.754891838 -1.2400737082 -0.429912888 -0.042880265 -0.310582498
## [76,] -0.481223384 -1.6568091126 -0.571446610 -0.006497154 -0.192064821
## [77,] 2.558238550 -1.0424716569 -0.427627827 0.486928124 0.108041894
## [78,] 0.386470146 -0.3471305811 -0.256096038 -0.679098947 -0.536365658
## [79,] -1.938679135 -0.4597308466 0.447786452 0.041224615 -0.940505437
## [80,] -1.571049075 -0.7421068599 0.469273049 -0.004676726 -0.818362895
## [81,] 0.698492042 -0.9579087491 -0.593217851 -0.622341584 -0.176788790
## [82,] 1.624233260 1.7798689279 0.043418886 0.078660892 -0.134865204
## [83,] 2.176853333 0.6127418112 0.173218811 0.170585917 -0.133478985
## [84,] 2.893275800 0.0806549771 0.486302312 -1.253010841 -0.799826228
## [85,] 2.416996108 0.8357356176 -0.098232297 -0.604840512 -0.526701751
## [86,] 2.858120641 0.0763196535 0.439038875 -1.146151559 -0.866330538
## [87,] -0.984400494 2.7255460689 -1.012165889 -0.460020248 0.315200326
## [88,] -0.777211751 2.5177786990 -1.123760966 -0.245997442 0.458817505
## [89,] -0.693563623 2.0760260059 -1.502783625 0.455165336 0.442330872
## [90,] -1.169314595 2.7905099635 -0.947255306 -0.106219366 0.474282792
## [91,] 1.732591485 1.0815550088 -1.901958309 0.175116312 -1.990578094
## [92,] 3.649191948 0.0991618026 -1.231637170 1.956854580 -1.204831994
## [93,] -1.244916810 -2.1504356005 -0.024574979 0.142930733 -0.054188461
## [94,] -1.002282591 -1.8278480814 0.020435420 0.770764334 -0.358235807
## [95,] -1.568654689 -1.9758843644 0.251618881 -0.006462161 -0.226801785
## [96,] -0.877969904 -2.3379779556 -0.773824321 0.560543518 -0.053605710
## [97,] -1.182250463 -2.2478339755 -0.330734031 0.257924885 0.182840392
## [98,] -0.483619842 -1.7425300497 -1.185686907 -0.693910238 0.514012127
## [99,] 0.845615004 -2.0875022681 -2.817962762 0.924274794 -0.049245679
## [100,] -0.048343429 -2.1371767093 -0.322268437 0.811767158 0.894031818
## [101,] -0.587368078 -1.8086869519 -0.580721312 0.836763536 0.550413107
## [102,] 0.250655950 -1.7188864664 -0.596870964 -0.638490781 0.403688528
## [103,] 0.279269891 -1.2068536914 -0.511648116 -0.718464790 0.400509068
## [104,] 1.438860748 0.0007382128 -1.482703865 -1.156823833 0.578599427
## [105,] 2.720853435 0.0579177824 -1.687304620 -0.216494783 0.663302905
## [106,] 1.494884432 -0.3796501178 -1.830187439 -0.608209909 0.480096061
## [107,] 2.377565841 0.2199104730 -0.796701983 -0.010000666 0.563415423
## [108,] -0.712774538 2.0242653299 -1.075755760 -0.451663010 -0.249650202
## [109,] -0.371311352 1.6944390827 -0.886390077 -0.397624467 -0.256006594
## [110,] 0.655317902 1.8903871660 0.393545938 1.207170902 0.015825133
## [111,] -1.191217704 0.4490428537 -2.438682619 0.630712273 -0.548877125
## [112,] -0.294420241 -0.7746409245 -2.517613173 1.088253255 -0.619797861
## [113,] -0.504620967 -0.7169046667 -2.745025510 1.017599068 -0.133502686
## [114,] -2.037601031 -0.8989471892 -0.397771498 -2.229720409 0.303929686
## [115,] -1.392618397 -0.7707606542 -0.935645870 -0.113985431 0.233852377
## [116,] -1.522184879 -0.5081826534 -1.006476515 -0.095942061 0.416729401
## [117,] 0.243056712 -1.3522783207 -2.871464992 1.025608844 -0.088930048
## [118,] -0.242637192 3.8072064452 3.520601285 3.013532431 0.826966318
## [119,] -1.234472058 2.5472987285 -0.584276784 0.300969308 -0.268877907
## [120,] -1.051500395 2.3530117797 0.837842678 0.778126484 -0.598463442
## [121,] -0.385992363 2.7746617263 3.165889291 1.989589410 0.771261839
## [122,] 1.993994069 -1.0443822850 2.202013244 -0.060165184 -1.467970112
## [123,] 0.893527003 -0.9821496223 2.441104843 -1.835751697 -1.144161720
## [124,] 1.452017254 -1.2269680811 2.254531908 -1.364491169 -1.422601647
## [125,] 0.732746280 -1.1219639011 2.305809670 -1.760925100 -1.203000518
## [126,] -0.499559924 0.5571001065 0.282048563 -1.005055174 -0.524935227
## [127,] -1.873865792 1.6720270140 -0.144223833 -0.363595015 0.253052017
## [128,] -2.360899858 1.1953656281 0.355591662 -0.178246210 -0.170433028
## [129,] -2.427026348 0.7525405535 0.550395858 0.250927746 -0.303155786
## PC6 PC7 PC8 PC9
## [1,] 0.2392498507 -0.431464195 0.243083289 -0.143778968
## [2,] 0.0930351866 0.064082296 0.474974308 -0.043481087
## [3,] -0.3297019194 0.203855434 -0.274567373 -0.050483163
## [4,] 0.0092686648 0.015856104 0.004064807 -0.102713767
## [5,] 0.2153417873 -0.353444892 0.219941728 -0.120149893
## [6,] 0.3699533749 0.075365616 0.296060158 0.122846968
## [7,] 0.3269294711 0.065908657 0.372795039 0.122537436
## [8,] -0.2110245161 -0.136086896 -0.248752470 0.091201448
## [9,] -0.3678170434 0.290597114 -0.379704108 0.128224046
## [10,] 0.3247920944 -0.066753603 0.420484635 0.458473364
## [11,] 0.2466552490 0.085466546 -0.586730686 -0.410147482
## [12,] -1.0403413482 0.480448719 0.374139656 -0.019014646
## [13,] -0.7604364704 0.337967478 0.140801807 -0.066748291
## [14,] -0.0863594906 -0.016400593 -0.140875914 -0.284545975
## [15,] -0.2597606938 0.104099570 -0.009171909 -0.114953452
## [16,] -0.4826314145 -0.610303794 -0.307319299 0.197642123
## [17,] -0.8238042703 -1.180281514 -0.931727079 0.208814590
## [18,] 0.0835278239 -0.307791962 -0.003715411 -0.210905512
## [19,] -0.0467292310 -0.368538423 -0.151252782 -0.387197932
## [20,] -0.2357731431 -0.765922520 -0.021753087 0.091016736
## [21,] -0.9080652565 0.016549022 0.220428858 -0.116778346
## [22,] -1.7583953440 0.520258350 -0.480681106 -0.429661589
## [23,] -0.6177556203 0.066548837 0.128470499 -0.271833568
## [24,] -0.3626023411 0.027936473 0.422007870 0.083213092
## [25,] -0.2363021838 0.273025291 -0.083871364 0.342036656
## [26,] 0.0245055087 0.392842305 0.001067156 0.414587306
## [27,] 0.1411209072 0.198831194 0.189257985 0.164451241
## [28,] 0.0782455331 0.169054972 0.252350249 -0.004879045
## [29,] -0.6987440644 0.187157676 0.010710289 -0.004550123
## [30,] -0.9154359690 0.588713567 0.158470008 0.754220748
## [31,] -0.1552617317 -0.068600012 0.184566469 0.023598479
## [32,] 0.3262028363 -0.346872756 0.067777942 0.132888248
## [33,] -0.3998936109 0.139609643 -0.082952314 -0.062177706
## [34,] -0.2534683819 -0.112144925 -0.032414098 -0.565775018
## [35,] -0.1448822629 0.003430294 -0.005985788 -0.232031620
## [36,] -0.1115730876 -0.391140899 -0.099628518 -0.220107936
## [37,] 0.2746789109 -0.136563793 0.084489562 -0.172922177
## [38,] -0.2716641949 0.426367926 -0.627291885 -0.082411245
## [39,] -0.0650790848 -0.018433397 0.060103306 -0.277590821
## [40,] 0.2802813038 0.042763696 0.267851038 -0.177241128
## [41,] 0.9903786349 0.119603602 0.059365786 -0.349507591
## [42,] 1.2413789743 0.433232550 0.420356174 -0.224145026
## [43,] 0.7048557087 0.052311898 -0.537627597 1.277060636
## [44,] 1.2860802893 -0.082911395 -0.162389145 -0.203109278
## [45,] 1.3950750935 0.125959302 -1.104437000 -0.222371692
## [46,] 1.5641330689 0.472775136 -0.795967616 -0.048462006
## [47,] 0.5431145699 -0.171251346 -0.362538921 -0.095115785
## [48,] 0.6445203383 -0.097395193 -0.461212843 -0.061114764
## [49,] -0.4485934288 -0.808374372 0.030870783 0.199614089
## [50,] -0.5390239381 -0.401496407 -0.050106311 0.084900374
## [51,] -1.0015808045 -0.127722538 0.697821830 -0.682471650
## [52,] -0.8160710080 -0.155745862 -0.117644982 -0.321917643
## [53,] -0.3666827957 0.580879640 -0.175277198 -0.096449171
## [54,] -0.0818333791 0.517384290 -0.165851871 -0.342431659
## [55,] 0.5812070018 -0.237558775 -0.371068372 -0.455760605
## [56,] 1.1521921126 -0.762264542 -0.070057528 -0.433412906
## [57,] -0.2107213676 -0.208725761 0.397899621 0.165854092
## [58,] -0.0813149023 -0.515793955 0.320914079 -0.246026509
## [59,] -0.4108050584 0.391909616 0.213276975 0.101437682
## [60,] -0.6427138804 0.280055612 0.130122481 -0.024823999
## [61,] -0.3299351779 0.049103220 -0.616403135 0.143983021
## [62,] 0.0969336915 -0.485416847 -0.917787378 0.004065495
## [63,] 0.3180959780 -0.211413159 -0.799794549 0.027767866
## [64,] 0.5203375563 -0.880039988 -0.128112884 0.988547823
## [65,] 0.6006642660 0.170412457 0.055793989 -0.088719728
## [66,] 0.6519682665 0.096914484 -0.392543412 -0.365221745
## [67,] 0.8486719776 -0.168738914 -0.249780677 -0.180333801
## [68,] 0.8329573703 -0.133428901 0.081584658 -0.077202887
## [69,] 0.6104804931 0.130047710 0.289910652 0.077874068
## [70,] -0.9870894175 -0.052370758 -0.335478832 0.102207803
## [71,] -1.2441672413 0.056851902 -0.659308206 0.210714116
## [72,] -1.0373635880 -0.069617600 -0.548428617 0.451409063
## [73,] -0.9259596761 -0.008872934 -0.514781883 0.376222366
## [74,] -0.4806714451 -0.424620168 0.361942577 0.108782469
## [75,] -0.5994892144 -0.392281149 0.270559201 0.052547648
## [76,] -0.7598404011 -0.292912323 0.341996371 0.103525045
## [77,] -0.1360408442 -0.184348349 -0.139487794 -0.394970617
## [78,] 0.0346775450 0.104948143 0.082021124 -0.230369975
## [79,] -0.3342552482 -0.963995687 0.097587075 0.258109143
## [80,] -0.5384303559 -0.890647392 0.082360843 0.301592034
## [81,] -0.0563657415 0.104850720 0.105609932 -0.100222689
## [82,] 1.6239557813 0.466659100 -0.205317300 0.195790552
## [83,] 1.2541423247 0.659001771 0.111934643 0.671430869
## [84,] 0.3901378952 0.124671721 -0.083234777 0.443341630
## [85,] 1.2059701150 0.600575985 -0.105598155 0.548866245
## [86,] 0.4091838079 0.035320734 -0.102067547 0.477694702
## [87,] -0.0862789273 0.302271704 0.006025155 -0.275812563
## [88,] -0.0900433029 0.746234951 0.238018641 -0.007425653
## [89,] 0.1791089101 1.185261227 0.501457598 0.516937117
## [90,] -0.1654530017 1.273856514 0.070815768 -0.113420851
## [91,] -0.1959503266 -0.654984708 0.721974180 -0.051482623
## [92,] -0.0932412900 -0.379367131 0.367403945 0.938153940
## [93,] 0.2142611072 0.169126983 -0.079940173 -0.117174646
## [94,] 0.6307217743 0.379044936 0.101585570 -0.155057018
## [95,] 0.3780769978 0.099039349 0.216846276 -0.091839421
## [96,] 0.5580800269 0.447262590 0.278484394 -0.131816925
## [97,] 0.4672611800 0.135636174 -0.017000552 -0.084374404
## [98,] -0.5171184392 -0.661254728 -0.292953682 -0.243090381
## [99,] -0.0700958499 -0.154662676 -0.415296187 -0.398627015
## [100,] -0.7037919648 0.492580677 -0.214130729 -0.369111135
## [101,] -0.6963295917 0.045432992 -0.355494676 0.008350379
## [102,] -0.1093075402 -0.316409482 0.284131500 0.054369594
## [103,] 0.0364358326 -0.021875265 0.210264629 -0.414195733
## [104,] 0.5771080352 -0.498795695 0.600636040 -0.209537111
## [105,] 1.3822507376 0.102837607 -0.301745224 -0.155782483
## [106,] 0.5129625786 -0.502233390 0.331532280 -0.108776138
## [107,] 1.0023656570 -0.240006067 -0.132828934 -0.140808724
## [108,] -0.0740488207 0.133813665 0.216851065 -0.049088869
## [109,] -0.1525464010 0.064872773 0.289401300 -0.012300609
## [110,] 0.1040341264 -0.314776326 0.709182614 -0.027464618
## [111,] 0.3459221986 -0.147885906 -0.525238791 -0.174584497
## [112,] 0.3461436254 -0.462793372 0.295832072 0.169626253
## [113,] 0.1990377465 0.306644588 -0.248957426 0.003301457
## [114,] -0.6849441153 0.748731152 0.387940456 -0.009710346
## [115,] 0.4789851038 -0.290454689 0.251462381 0.032963609
## [116,] 0.4769377292 -0.139210048 0.123201257 -0.134130214
## [117,] 0.5568338594 0.854690706 0.064946521 0.128384416
## [118,] 0.1167063560 -0.393587273 0.620452262 -0.520433582
## [119,] -0.2499983431 -0.720699482 0.482604381 0.254303757
## [120,] 0.2981387726 -0.510146306 0.492883910 0.254054080
## [121,] 0.6009306951 -0.289032488 0.776777268 0.186862716
## [122,] -0.4449584306 0.734541125 0.492492679 -0.207546157
## [123,] -0.0517613842 0.297079618 0.115591871 0.130199523
## [124,] 0.0005872656 0.522569798 0.359778541 0.024064282
## [125,] -0.2529304562 0.043739373 0.029471724 0.191360297
## [126,] -1.1701690753 1.191552982 0.066937436 0.079912269
## [127,] -0.7478348228 -0.248449075 -0.138836979 0.198553188
## [128,] -0.9103565477 0.193351617 -0.548310100 0.013560909
## [129,] -0.9581814591 0.164933125 -0.539375991 0.125784832## rotate the pca (arbitrary, but wanted to conform visualizations with previous work)
pca_nerr$rotation[, c(2,3)] <- pca_nerr$rotation[, c(2,3)] * -1
pca_nerr$x[, c(2,3)] <- pca_nerr$x[, c(2,3)] * -1
pca_nerr$
pca_nerr## NULLpca_nerr$rotation## PC1 PC2 PC3 PC4 PC5
## SpCond -0.47585553 0.10562380 0.369142363 -0.141788252 -0.1013437331
## Temp -0.14102731 0.57419888 -0.232807536 -0.002267199 -0.1173393145
## DO 0.07171512 -0.57662754 -0.180686050 -0.324798789 -0.0164644283
## pH -0.40576069 -0.08797909 0.138698800 -0.619283992 -0.2341459091
## Turb 0.43548332 0.32300071 0.008433355 -0.216721723 0.2498698202
## Chla 0.29325701 0.32421987 -0.109959369 -0.639363999 0.0005773586
## NH4 0.30422790 0.13142462 0.469706271 0.137706574 -0.7199640464
## NO23 0.45082453 -0.30293329 0.037769522 -0.106625058 -0.2392896835
## PO4 0.11155828 -0.02026380 0.723489502 -0.069263298 0.5318105938
## PC6 PC7 PC8 PC9
## SpCond -0.24626090 0.01484365 0.69135209 -0.23860450
## Temp 0.31736983 0.11528470 -0.19409288 -0.65631374
## DO -0.17543755 -0.38813613 -0.08889209 -0.57845920
## pH 0.47681893 -0.07602463 -0.22961813 0.29014323
## Turb 0.31688328 -0.58116855 0.39028419 0.07782562
## Chla -0.53367196 0.29780324 -0.08817841 0.08207387
## NH4 -0.13910680 -0.26781135 -0.19794148 -0.04453308
## NO23 0.41239471 0.55782809 0.36513120 -0.14272809
## PO4 0.07652751 0.14394777 -0.30188600 -0.24160832write.csv(pca_nerr$rotation, 'dataout/swmp_pca_loadings_spc.csv')
pca_nerr$x## PC1 PC2 PC3 PC4 PC5
## [1,] -0.200402235 1.3716284766 1.156218215 -0.319546336 0.218042300
## [2,] -0.101213563 1.3688465409 0.407624370 -0.435015947 0.474825539
## [3,] 2.251106345 1.8307450578 0.576056899 1.093229014 1.122228614
## [4,] 1.130268086 1.5347449068 0.749682819 0.097642905 0.688009239
## [5,] -0.090838185 1.3742605387 1.092429822 0.042622516 0.136904731
## [6,] -0.668846285 0.7542562318 -1.336204721 -0.719092436 -1.032696555
## [7,] -0.633027479 0.7532834813 -1.675570901 -1.053931619 -0.570004705
## [8,] 0.587244930 1.3408750890 -1.893257460 -0.420240900 -0.659889430
## [9,] 0.456143686 1.2600239113 -2.019446114 -0.066713981 -0.568200924
## [10,] -1.556844449 0.8599200287 -1.565632267 -0.822383041 -0.275651020
## [11,] 2.231707491 -0.9245124975 0.322147025 0.847785325 0.380157846
## [12,] 0.993945443 -0.4138394685 -1.277215629 0.385101977 1.657726094
## [13,] 2.996807469 0.4093413434 -0.620555242 1.530779719 0.532089229
## [14,] 2.578889729 0.0126943829 -1.720134459 -1.638732511 -0.643327845
## [15,] 2.972013063 -0.4733720203 -0.427812743 0.211414585 0.056120173
## [16,] 0.202135191 0.1437396170 -0.299160519 -0.861173464 0.103111402
## [17,] -1.317250949 -0.6364755584 -0.559372478 -0.820208903 -0.499045491
## [18,] 2.504200708 0.0420175524 -0.668102102 0.396502786 0.749849857
## [19,] 2.650104405 -0.0333424818 -0.418241010 0.299140842 0.611537175
## [20,] 1.779428554 0.6287036473 0.230970450 -0.689960289 0.572103437
## [21,] 3.500890689 0.2477542409 -0.757957832 -0.601802078 0.432152438
## [22,] 3.191791717 -0.0782592771 -0.685929154 0.078244142 -0.006123801
## [23,] 3.763380186 0.0760233949 0.058890355 -0.158826102 -0.172941476
## [24,] 3.280975587 0.4972977652 1.043869017 0.148998216 -0.169150158
## [25,] -0.682143036 0.3024112143 1.779002581 -0.112699864 -0.125511431
## [26,] -0.442781406 0.3122467814 1.715660920 -0.768751512 -0.602418359
## [27,] -0.361898273 -0.2507669022 1.672341817 -0.425375281 -0.531479672
## [28,] -0.469112447 -1.2469059008 1.548993174 -0.348276211 -0.638444749
## [29,] -0.403608782 1.4954651152 -1.565020771 0.488041905 0.702323319
## [30,] 0.008793802 2.4950773359 -0.743109306 1.863872253 0.066027246
## [31,] -1.084534932 0.9989652274 -1.734490439 -0.465565086 1.035095218
## [32,] -1.473759318 0.8508444123 -1.599950598 -1.280485174 0.811326546
## [33,] -0.450560532 -1.1217288344 0.372265258 -0.712758740 -0.029546294
## [34,] 0.668614015 -1.1084910135 -0.523134638 0.920650583 -0.353576626
## [35,] 0.570130570 -0.5241760111 0.974704554 -0.311168462 -0.195713944
## [36,] 1.239618709 -0.2009062917 1.255586508 -0.407288408 -0.754204112
## [37,] -1.444502463 1.1671233889 0.372951792 -0.252464884 -0.349625437
## [38,] 0.113926855 1.9020131198 0.180164217 0.598238574 0.588820774
## [39,] -0.446348680 1.6793025968 0.469757162 0.265813800 0.088469670
## [40,] -0.995893112 1.3872279768 0.483224963 -0.240095207 -0.281683631
## [41,] -3.027964976 0.2234141996 -0.721362143 0.801235308 -0.633435456
## [42,] -3.835626745 0.0137166576 -1.624765921 0.697734421 0.794234857
## [43,] -0.158808712 2.6395082069 -1.088743734 3.418297230 1.917929516
## [44,] 1.977975795 -2.1824657315 0.103368017 -0.210896570 0.337608506
## [45,] 0.592960851 -2.2460243461 0.145075515 0.415554334 -0.071304835
## [46,] -0.311428188 -3.2497037510 -1.471969521 -0.287988139 -0.461674468
## [47,] 1.620985986 -1.1036946924 -0.826206821 0.280418832 -0.198529765
## [48,] 1.373952902 -1.3364978751 -0.848868152 0.160140710 -0.184280539
## [49,] -1.093629908 -0.3834892787 0.291625481 -0.974116310 0.744920454
## [50,] -0.969655799 -0.2534052668 0.190459330 -0.807629787 0.729378247
## [51,] 2.327756907 -0.8003908611 -1.879419408 2.266133651 1.188670257
## [52,] 0.773992992 -0.8162425813 -0.006019797 0.479491312 0.081344354
## [53,] -2.225347032 2.4733204839 -0.154754492 1.223835897 -1.511682740
## [54,] -2.783970485 1.5595089404 -0.735263984 1.555247813 -2.261474309
## [55,] -3.589013613 0.7308212872 -0.932792928 1.447992394 -2.114486266
## [56,] -3.377015091 0.7617413519 -0.693250289 1.705113946 -1.966007942
## [57,] -1.098870382 -3.5338504324 1.081945910 -0.130526372 0.062650001
## [58,] -1.068722248 -3.4291910363 0.497705539 -0.829821368 0.275441956
## [59,] -1.432547065 -3.6603403021 0.898474939 -0.110579070 0.025737292
## [60,] -1.293086085 -3.7749664712 0.804811104 -0.360103220 -0.079252269
## [61,] 1.820782933 -1.1043111257 -1.015708140 -0.636520991 -0.663248537
## [62,] 1.716814118 -1.0308810119 -0.411319244 -0.137532040 -1.434833366
## [63,] 0.687219935 -0.9388947705 -1.453922063 -0.119340969 -0.075809400
## [64,] 1.738179687 0.8672086429 -0.545401703 0.369344054 1.213091293
## [65,] -2.047181955 0.8432391422 -0.849468340 -1.376572855 1.507255639
## [66,] -1.491216160 0.9825672954 -0.457046271 -1.268093769 1.789807668
## [67,] -1.210164987 0.9596908541 -0.662321087 -1.439722041 2.219623981
## [68,] -1.641186601 1.0075826426 -0.849343395 -1.597527957 1.887088237
## [69,] -2.360956882 0.8693036050 -1.141307019 -0.985282761 0.843374489
## [70,] -1.547947533 -0.5694738280 0.594717247 1.162334194 0.664706741
## [71,] -2.054506895 -1.8437973242 0.421696017 -0.029493929 0.454390342
## [72,] -2.450808989 -1.9074444487 0.350663902 0.033744764 0.480026709
## [73,] -2.615856736 -1.8977266476 0.061879094 0.015686479 0.720067705
## [74,] -0.698045232 1.2542467284 0.554445303 0.039682384 -0.326488311
## [75,] -0.754891838 1.2400737082 0.429912888 -0.042880265 -0.310582498
## [76,] -0.481223384 1.6568091126 0.571446610 -0.006497154 -0.192064821
## [77,] 2.558238550 1.0424716569 0.427627827 0.486928124 0.108041894
## [78,] 0.386470146 0.3471305811 0.256096038 -0.679098947 -0.536365658
## [79,] -1.938679135 0.4597308466 -0.447786452 0.041224615 -0.940505437
## [80,] -1.571049075 0.7421068599 -0.469273049 -0.004676726 -0.818362895
## [81,] 0.698492042 0.9579087491 0.593217851 -0.622341584 -0.176788790
## [82,] 1.624233260 -1.7798689279 -0.043418886 0.078660892 -0.134865204
## [83,] 2.176853333 -0.6127418112 -0.173218811 0.170585917 -0.133478985
## [84,] 2.893275800 -0.0806549771 -0.486302312 -1.253010841 -0.799826228
## [85,] 2.416996108 -0.8357356176 0.098232297 -0.604840512 -0.526701751
## [86,] 2.858120641 -0.0763196535 -0.439038875 -1.146151559 -0.866330538
## [87,] -0.984400494 -2.7255460689 1.012165889 -0.460020248 0.315200326
## [88,] -0.777211751 -2.5177786990 1.123760966 -0.245997442 0.458817505
## [89,] -0.693563623 -2.0760260059 1.502783625 0.455165336 0.442330872
## [90,] -1.169314595 -2.7905099635 0.947255306 -0.106219366 0.474282792
## [91,] 1.732591485 -1.0815550088 1.901958309 0.175116312 -1.990578094
## [92,] 3.649191948 -0.0991618026 1.231637170 1.956854580 -1.204831994
## [93,] -1.244916810 2.1504356005 0.024574979 0.142930733 -0.054188461
## [94,] -1.002282591 1.8278480814 -0.020435420 0.770764334 -0.358235807
## [95,] -1.568654689 1.9758843644 -0.251618881 -0.006462161 -0.226801785
## [96,] -0.877969904 2.3379779556 0.773824321 0.560543518 -0.053605710
## [97,] -1.182250463 2.2478339755 0.330734031 0.257924885 0.182840392
## [98,] -0.483619842 1.7425300497 1.185686907 -0.693910238 0.514012127
## [99,] 0.845615004 2.0875022681 2.817962762 0.924274794 -0.049245679
## [100,] -0.048343429 2.1371767093 0.322268437 0.811767158 0.894031818
## [101,] -0.587368078 1.8086869519 0.580721312 0.836763536 0.550413107
## [102,] 0.250655950 1.7188864664 0.596870964 -0.638490781 0.403688528
## [103,] 0.279269891 1.2068536914 0.511648116 -0.718464790 0.400509068
## [104,] 1.438860748 -0.0007382128 1.482703865 -1.156823833 0.578599427
## [105,] 2.720853435 -0.0579177824 1.687304620 -0.216494783 0.663302905
## [106,] 1.494884432 0.3796501178 1.830187439 -0.608209909 0.480096061
## [107,] 2.377565841 -0.2199104730 0.796701983 -0.010000666 0.563415423
## [108,] -0.712774538 -2.0242653299 1.075755760 -0.451663010 -0.249650202
## [109,] -0.371311352 -1.6944390827 0.886390077 -0.397624467 -0.256006594
## [110,] 0.655317902 -1.8903871660 -0.393545938 1.207170902 0.015825133
## [111,] -1.191217704 -0.4490428537 2.438682619 0.630712273 -0.548877125
## [112,] -0.294420241 0.7746409245 2.517613173 1.088253255 -0.619797861
## [113,] -0.504620967 0.7169046667 2.745025510 1.017599068 -0.133502686
## [114,] -2.037601031 0.8989471892 0.397771498 -2.229720409 0.303929686
## [115,] -1.392618397 0.7707606542 0.935645870 -0.113985431 0.233852377
## [116,] -1.522184879 0.5081826534 1.006476515 -0.095942061 0.416729401
## [117,] 0.243056712 1.3522783207 2.871464992 1.025608844 -0.088930048
## [118,] -0.242637192 -3.8072064452 -3.520601285 3.013532431 0.826966318
## [119,] -1.234472058 -2.5472987285 0.584276784 0.300969308 -0.268877907
## [120,] -1.051500395 -2.3530117797 -0.837842678 0.778126484 -0.598463442
## [121,] -0.385992363 -2.7746617263 -3.165889291 1.989589410 0.771261839
## [122,] 1.993994069 1.0443822850 -2.202013244 -0.060165184 -1.467970112
## [123,] 0.893527003 0.9821496223 -2.441104843 -1.835751697 -1.144161720
## [124,] 1.452017254 1.2269680811 -2.254531908 -1.364491169 -1.422601647
## [125,] 0.732746280 1.1219639011 -2.305809670 -1.760925100 -1.203000518
## [126,] -0.499559924 -0.5571001065 -0.282048563 -1.005055174 -0.524935227
## [127,] -1.873865792 -1.6720270140 0.144223833 -0.363595015 0.253052017
## [128,] -2.360899858 -1.1953656281 -0.355591662 -0.178246210 -0.170433028
## [129,] -2.427026348 -0.7525405535 -0.550395858 0.250927746 -0.303155786
## PC6 PC7 PC8 PC9
## [1,] 0.2392498507 -0.431464195 0.243083289 -0.143778968
## [2,] 0.0930351866 0.064082296 0.474974308 -0.043481087
## [3,] -0.3297019194 0.203855434 -0.274567373 -0.050483163
## [4,] 0.0092686648 0.015856104 0.004064807 -0.102713767
## [5,] 0.2153417873 -0.353444892 0.219941728 -0.120149893
## [6,] 0.3699533749 0.075365616 0.296060158 0.122846968
## [7,] 0.3269294711 0.065908657 0.372795039 0.122537436
## [8,] -0.2110245161 -0.136086896 -0.248752470 0.091201448
## [9,] -0.3678170434 0.290597114 -0.379704108 0.128224046
## [10,] 0.3247920944 -0.066753603 0.420484635 0.458473364
## [11,] 0.2466552490 0.085466546 -0.586730686 -0.410147482
## [12,] -1.0403413482 0.480448719 0.374139656 -0.019014646
## [13,] -0.7604364704 0.337967478 0.140801807 -0.066748291
## [14,] -0.0863594906 -0.016400593 -0.140875914 -0.284545975
## [15,] -0.2597606938 0.104099570 -0.009171909 -0.114953452
## [16,] -0.4826314145 -0.610303794 -0.307319299 0.197642123
## [17,] -0.8238042703 -1.180281514 -0.931727079 0.208814590
## [18,] 0.0835278239 -0.307791962 -0.003715411 -0.210905512
## [19,] -0.0467292310 -0.368538423 -0.151252782 -0.387197932
## [20,] -0.2357731431 -0.765922520 -0.021753087 0.091016736
## [21,] -0.9080652565 0.016549022 0.220428858 -0.116778346
## [22,] -1.7583953440 0.520258350 -0.480681106 -0.429661589
## [23,] -0.6177556203 0.066548837 0.128470499 -0.271833568
## [24,] -0.3626023411 0.027936473 0.422007870 0.083213092
## [25,] -0.2363021838 0.273025291 -0.083871364 0.342036656
## [26,] 0.0245055087 0.392842305 0.001067156 0.414587306
## [27,] 0.1411209072 0.198831194 0.189257985 0.164451241
## [28,] 0.0782455331 0.169054972 0.252350249 -0.004879045
## [29,] -0.6987440644 0.187157676 0.010710289 -0.004550123
## [30,] -0.9154359690 0.588713567 0.158470008 0.754220748
## [31,] -0.1552617317 -0.068600012 0.184566469 0.023598479
## [32,] 0.3262028363 -0.346872756 0.067777942 0.132888248
## [33,] -0.3998936109 0.139609643 -0.082952314 -0.062177706
## [34,] -0.2534683819 -0.112144925 -0.032414098 -0.565775018
## [35,] -0.1448822629 0.003430294 -0.005985788 -0.232031620
## [36,] -0.1115730876 -0.391140899 -0.099628518 -0.220107936
## [37,] 0.2746789109 -0.136563793 0.084489562 -0.172922177
## [38,] -0.2716641949 0.426367926 -0.627291885 -0.082411245
## [39,] -0.0650790848 -0.018433397 0.060103306 -0.277590821
## [40,] 0.2802813038 0.042763696 0.267851038 -0.177241128
## [41,] 0.9903786349 0.119603602 0.059365786 -0.349507591
## [42,] 1.2413789743 0.433232550 0.420356174 -0.224145026
## [43,] 0.7048557087 0.052311898 -0.537627597 1.277060636
## [44,] 1.2860802893 -0.082911395 -0.162389145 -0.203109278
## [45,] 1.3950750935 0.125959302 -1.104437000 -0.222371692
## [46,] 1.5641330689 0.472775136 -0.795967616 -0.048462006
## [47,] 0.5431145699 -0.171251346 -0.362538921 -0.095115785
## [48,] 0.6445203383 -0.097395193 -0.461212843 -0.061114764
## [49,] -0.4485934288 -0.808374372 0.030870783 0.199614089
## [50,] -0.5390239381 -0.401496407 -0.050106311 0.084900374
## [51,] -1.0015808045 -0.127722538 0.697821830 -0.682471650
## [52,] -0.8160710080 -0.155745862 -0.117644982 -0.321917643
## [53,] -0.3666827957 0.580879640 -0.175277198 -0.096449171
## [54,] -0.0818333791 0.517384290 -0.165851871 -0.342431659
## [55,] 0.5812070018 -0.237558775 -0.371068372 -0.455760605
## [56,] 1.1521921126 -0.762264542 -0.070057528 -0.433412906
## [57,] -0.2107213676 -0.208725761 0.397899621 0.165854092
## [58,] -0.0813149023 -0.515793955 0.320914079 -0.246026509
## [59,] -0.4108050584 0.391909616 0.213276975 0.101437682
## [60,] -0.6427138804 0.280055612 0.130122481 -0.024823999
## [61,] -0.3299351779 0.049103220 -0.616403135 0.143983021
## [62,] 0.0969336915 -0.485416847 -0.917787378 0.004065495
## [63,] 0.3180959780 -0.211413159 -0.799794549 0.027767866
## [64,] 0.5203375563 -0.880039988 -0.128112884 0.988547823
## [65,] 0.6006642660 0.170412457 0.055793989 -0.088719728
## [66,] 0.6519682665 0.096914484 -0.392543412 -0.365221745
## [67,] 0.8486719776 -0.168738914 -0.249780677 -0.180333801
## [68,] 0.8329573703 -0.133428901 0.081584658 -0.077202887
## [69,] 0.6104804931 0.130047710 0.289910652 0.077874068
## [70,] -0.9870894175 -0.052370758 -0.335478832 0.102207803
## [71,] -1.2441672413 0.056851902 -0.659308206 0.210714116
## [72,] -1.0373635880 -0.069617600 -0.548428617 0.451409063
## [73,] -0.9259596761 -0.008872934 -0.514781883 0.376222366
## [74,] -0.4806714451 -0.424620168 0.361942577 0.108782469
## [75,] -0.5994892144 -0.392281149 0.270559201 0.052547648
## [76,] -0.7598404011 -0.292912323 0.341996371 0.103525045
## [77,] -0.1360408442 -0.184348349 -0.139487794 -0.394970617
## [78,] 0.0346775450 0.104948143 0.082021124 -0.230369975
## [79,] -0.3342552482 -0.963995687 0.097587075 0.258109143
## [80,] -0.5384303559 -0.890647392 0.082360843 0.301592034
## [81,] -0.0563657415 0.104850720 0.105609932 -0.100222689
## [82,] 1.6239557813 0.466659100 -0.205317300 0.195790552
## [83,] 1.2541423247 0.659001771 0.111934643 0.671430869
## [84,] 0.3901378952 0.124671721 -0.083234777 0.443341630
## [85,] 1.2059701150 0.600575985 -0.105598155 0.548866245
## [86,] 0.4091838079 0.035320734 -0.102067547 0.477694702
## [87,] -0.0862789273 0.302271704 0.006025155 -0.275812563
## [88,] -0.0900433029 0.746234951 0.238018641 -0.007425653
## [89,] 0.1791089101 1.185261227 0.501457598 0.516937117
## [90,] -0.1654530017 1.273856514 0.070815768 -0.113420851
## [91,] -0.1959503266 -0.654984708 0.721974180 -0.051482623
## [92,] -0.0932412900 -0.379367131 0.367403945 0.938153940
## [93,] 0.2142611072 0.169126983 -0.079940173 -0.117174646
## [94,] 0.6307217743 0.379044936 0.101585570 -0.155057018
## [95,] 0.3780769978 0.099039349 0.216846276 -0.091839421
## [96,] 0.5580800269 0.447262590 0.278484394 -0.131816925
## [97,] 0.4672611800 0.135636174 -0.017000552 -0.084374404
## [98,] -0.5171184392 -0.661254728 -0.292953682 -0.243090381
## [99,] -0.0700958499 -0.154662676 -0.415296187 -0.398627015
## [100,] -0.7037919648 0.492580677 -0.214130729 -0.369111135
## [101,] -0.6963295917 0.045432992 -0.355494676 0.008350379
## [102,] -0.1093075402 -0.316409482 0.284131500 0.054369594
## [103,] 0.0364358326 -0.021875265 0.210264629 -0.414195733
## [104,] 0.5771080352 -0.498795695 0.600636040 -0.209537111
## [105,] 1.3822507376 0.102837607 -0.301745224 -0.155782483
## [106,] 0.5129625786 -0.502233390 0.331532280 -0.108776138
## [107,] 1.0023656570 -0.240006067 -0.132828934 -0.140808724
## [108,] -0.0740488207 0.133813665 0.216851065 -0.049088869
## [109,] -0.1525464010 0.064872773 0.289401300 -0.012300609
## [110,] 0.1040341264 -0.314776326 0.709182614 -0.027464618
## [111,] 0.3459221986 -0.147885906 -0.525238791 -0.174584497
## [112,] 0.3461436254 -0.462793372 0.295832072 0.169626253
## [113,] 0.1990377465 0.306644588 -0.248957426 0.003301457
## [114,] -0.6849441153 0.748731152 0.387940456 -0.009710346
## [115,] 0.4789851038 -0.290454689 0.251462381 0.032963609
## [116,] 0.4769377292 -0.139210048 0.123201257 -0.134130214
## [117,] 0.5568338594 0.854690706 0.064946521 0.128384416
## [118,] 0.1167063560 -0.393587273 0.620452262 -0.520433582
## [119,] -0.2499983431 -0.720699482 0.482604381 0.254303757
## [120,] 0.2981387726 -0.510146306 0.492883910 0.254054080
## [121,] 0.6009306951 -0.289032488 0.776777268 0.186862716
## [122,] -0.4449584306 0.734541125 0.492492679 -0.207546157
## [123,] -0.0517613842 0.297079618 0.115591871 0.130199523
## [124,] 0.0005872656 0.522569798 0.359778541 0.024064282
## [125,] -0.2529304562 0.043739373 0.029471724 0.191360297
## [126,] -1.1701690753 1.191552982 0.066937436 0.079912269
## [127,] -0.7478348228 -0.248449075 -0.138836979 0.198553188
## [128,] -0.9103565477 0.193351617 -0.548310100 0.013560909
## [129,] -0.9581814591 0.164933125 -0.539375991 0.125784832#pca_nerr <- prcomp(df.n, center=FALSE, scale=FALSE)
pca_smry<-summary(pca_nerr)
pca_smry## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 1.7069 1.5262 1.2015 0.93117 0.79628 0.6342 0.43078
## Proportion of Variance 0.3237 0.2588 0.1604 0.09634 0.07045 0.0447 0.02062
## Cumulative Proportion 0.3237 0.5825 0.7429 0.83927 0.90973 0.9544 0.97504
## PC8 PC9
## Standard deviation 0.36606 0.30104
## Proportion of Variance 0.01489 0.01007
## Cumulative Proportion 0.98993 1.00000# str(pca_smry)
pca_smry$importance## PC1 PC2 PC3 PC4 PC5 PC6
## Standard deviation 1.706891 1.526237 1.201466 0.9311692 0.7962843 0.6342399
## Proportion of Variance 0.323720 0.258820 0.160390 0.0963400 0.0704500 0.0447000
## Cumulative Proportion 0.323720 0.582540 0.742930 0.8392700 0.9097300 0.9544200
## PC7 PC8 PC9
## Standard deviation 0.4307805 0.3660578 0.3010445
## Proportion of Variance 0.0206200 0.0148900 0.0100700
## Cumulative Proportion 0.9750400 0.9899300 1.0000000nerr_col<-'#05829C'
fviz_eig(pca_nerr,barfill = nerr_col,xlab = 'Principle Components',
barcolor = nerr_col,main='',)+
theme(axis.text=element_text(size=16),
axis.title=element_text(size=18,face="bold"))
Kaiser Criterion helps to establish number of Principle Components that explain enough variance. According to the criterion, one should use as many PCs, as there is number of eigenvalues which are higher than 1. (3 PCs in this case)
eig.val<-get_eigenvalue(pca_nerr)
eig.val## eigenvalue variance.percent cumulative.variance.percent
## Dim.1 2.91347653 32.371961 32.37196
## Dim.2 2.32939905 25.882212 58.25417
## Dim.3 1.44352138 16.039126 74.29330
## Dim.4 0.86707615 9.634179 83.92748
## Dim.5 0.63406864 7.045207 90.97269
## Dim.6 0.40226028 4.469559 95.44224
## Dim.7 0.18557184 2.061909 97.50415
## Dim.8 0.13399834 1.488870 98.99302
## Dim.9 0.09062779 1.006975 100.00000for(i in 1:3){
var<-get_pca_var(pca_nerr)
print(var$contrib)
plot(fviz_contrib(pca_nerr, "var", axes=i, xtickslab.rt=90,fill = nerr_col,
color = nerr_col)+
labs(title=paste("Contributions of variables to PC",i)) +
theme(
title=element_text(size=18),
axis.text=element_text(size=16),
axis.title=element_text(size=18,face="bold")), main = 'PC1')
}## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5 Dim.6
## SpCond 22.6438487 1.11563881 13.626608410 2.010390827 1.027055e+00 6.064443
## Temp 1.9888702 32.97043526 5.419934874 0.000514019 1.376851e+00 10.072361
## DO 0.5143059 33.24993243 3.264744855 10.549425338 2.710774e-02 3.077833
## pH 16.4641734 0.77403204 1.923735704 38.351266220 5.482431e+00 22.735630
## Turb 18.9645721 10.43294555 0.007112147 4.696830513 6.243493e+00 10.041502
## Chla 8.5999673 10.51185267 1.209106280 40.878632290 3.333429e-05 28.480576
## NH4 9.2554616 1.72724313 22.062398070 1.896310052 5.183482e+01 1.935070
## NO23 20.3242757 9.17685797 0.142653677 1.136890294 5.725955e+00 17.006940
## PO4 1.2445251 0.04106214 52.343705983 0.479740447 2.828225e+01 0.585646
## Dim.7 Dim.8 Dim.9
## SpCond 0.02203339 47.7967708 5.6932107
## Temp 1.32905630 3.7672044 43.0747726
## DO 15.06496564 0.7901804 33.4615044
## pH 0.57797449 5.2724487 8.4183092
## Turb 33.77568796 15.2321747 0.6056826
## Chla 8.86867715 0.7775432 0.6736121
## NH4 7.17229190 3.9180828 0.1983195
## NO23 31.11721727 13.3320793 2.0371309
## PO4 2.07209591 9.1135158 5.8374579
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5 Dim.6
## SpCond 22.6438487 1.11563881 13.626608410 2.010390827 1.027055e+00 6.064443
## Temp 1.9888702 32.97043526 5.419934874 0.000514019 1.376851e+00 10.072361
## DO 0.5143059 33.24993243 3.264744855 10.549425338 2.710774e-02 3.077833
## pH 16.4641734 0.77403204 1.923735704 38.351266220 5.482431e+00 22.735630
## Turb 18.9645721 10.43294555 0.007112147 4.696830513 6.243493e+00 10.041502
## Chla 8.5999673 10.51185267 1.209106280 40.878632290 3.333429e-05 28.480576
## NH4 9.2554616 1.72724313 22.062398070 1.896310052 5.183482e+01 1.935070
## NO23 20.3242757 9.17685797 0.142653677 1.136890294 5.725955e+00 17.006940
## PO4 1.2445251 0.04106214 52.343705983 0.479740447 2.828225e+01 0.585646
## Dim.7 Dim.8 Dim.9
## SpCond 0.02203339 47.7967708 5.6932107
## Temp 1.32905630 3.7672044 43.0747726
## DO 15.06496564 0.7901804 33.4615044
## pH 0.57797449 5.2724487 8.4183092
## Turb 33.77568796 15.2321747 0.6056826
## Chla 8.86867715 0.7775432 0.6736121
## NH4 7.17229190 3.9180828 0.1983195
## NO23 31.11721727 13.3320793 2.0371309
## PO4 2.07209591 9.1135158 5.8374579
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5 Dim.6
## SpCond 22.6438487 1.11563881 13.626608410 2.010390827 1.027055e+00 6.064443
## Temp 1.9888702 32.97043526 5.419934874 0.000514019 1.376851e+00 10.072361
## DO 0.5143059 33.24993243 3.264744855 10.549425338 2.710774e-02 3.077833
## pH 16.4641734 0.77403204 1.923735704 38.351266220 5.482431e+00 22.735630
## Turb 18.9645721 10.43294555 0.007112147 4.696830513 6.243493e+00 10.041502
## Chla 8.5999673 10.51185267 1.209106280 40.878632290 3.333429e-05 28.480576
## NH4 9.2554616 1.72724313 22.062398070 1.896310052 5.183482e+01 1.935070
## NO23 20.3242757 9.17685797 0.142653677 1.136890294 5.725955e+00 17.006940
## PO4 1.2445251 0.04106214 52.343705983 0.479740447 2.828225e+01 0.585646
## Dim.7 Dim.8 Dim.9
## SpCond 0.02203339 47.7967708 5.6932107
## Temp 1.32905630 3.7672044 43.0747726
## DO 15.06496564 0.7901804 33.4615044
## pH 0.57797449 5.2724487 8.4183092
## Turb 33.77568796 15.2321747 0.6056826
## Chla 8.86867715 0.7775432 0.6736121
## NH4 7.17229190 3.9180828 0.1983195
## NO23 31.11721727 13.3320793 2.0371309
## PO4 2.07209591 9.1135158 5.8374579
v<-c(1:3)
v.pair<-combn(v, 2)
v.pair## [,1] [,2] [,3]
## [1,] 1 1 2
## [2,] 2 3 3class(summary(pca_nerr))## [1] "summary.prcomp"str(summary(pca_nerr))## List of 6
## $ sdev : num [1:9] 1.707 1.526 1.201 0.931 0.796 ...
## $ rotation : num [1:9, 1:9] -0.4759 -0.141 0.0717 -0.4058 0.4355 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:9] "SpCond" "Temp" "DO" "pH" ...
## .. ..$ : chr [1:9] "PC1" "PC2" "PC3" "PC4" ...
## $ center : Named num [1:9] 31.421 18.791 7.268 7.68 0.887 ...
## ..- attr(*, "names")= chr [1:9] "SpCond" "Temp" "DO" "pH" ...
## $ scale : Named num [1:9] 19.775 5.224 1.469 0.379 0.436 ...
## ..- attr(*, "names")= chr [1:9] "SpCond" "Temp" "DO" "pH" ...
## $ x : num [1:129, 1:9] -0.2004 -0.1012 2.2511 1.1303 -0.0908 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : NULL
## .. ..$ : chr [1:9] "PC1" "PC2" "PC3" "PC4" ...
## $ importance: num [1:3, 1:9] 1.707 0.324 0.324 1.526 0.259 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:3] "Standard deviation" "Proportion of Variance" "Cumulative Proportion"
## .. ..$ : chr [1:9] "PC1" "PC2" "PC3" "PC4" ...
## - attr(*, "class")= chr "summary.prcomp"smry.pca_nerr<-summary(pca_nerr)
prop.var<-smry.pca_nerr$importance[2,]
for(c in 1:ncol(v.pair)){
pair<-v.pair[,c]
xlbl<-paste0('PC',pair[1],' (',round(prop.var[pair[1]]*100,digits=1),'%)')
ylbl<-paste0('PC',pair[2],' (',round(prop.var[pair[2]]*100,digits=1),'%)')
pl<-fviz_pca_var(pca_nerr,axes=pair,
col.var = "contrib", # Color by contributions to the PC
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping
title = " ",
labelsize = 10
)+ coord_fixed() + xlab(xlbl) +
ylab(ylbl) +
theme(axis.text=element_text(size=28),
axis.title=element_text(size=32,face="bold"))
print(pl)
}## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
v<-c(1:3)
v.pair<-combn(v, 2)
v.pair## [,1] [,2] [,3]
## [1,] 1 1 2
## [2,] 2 3 3for(c in 1:ncol(v.pair)){
pair<-v.pair[,c]
xlbl<-paste0('PC',pair[1],' (',round(prop.var[pair[1]]*100,digits=1),'%)')
ylbl<-paste0('PC',pair[2],' (',round(prop.var[pair[2]]*100,digits=1),'%)')
pl<-fviz_pca_var(pca_nerr,axes=pair,
#col.var = "contrib", # Color by contributions to the PC
#radient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping
title = " ",
labelsize = 10
)+ coord_fixed() + xlab(xlbl) +
ylab(ylbl) +
theme(axis.text=element_text(size=28),
axis.title=element_text(size=32,face="bold"))
print(pl)
}## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will
## replace the existing one.
stn_ids<-read.csv('data/stn_map_ids.csv',stringsAsFactors = F)
nerr_h_comp.stn_ids.mrg<-merge(nerr_h_comp,stn_ids,by.x='code',by.y='code',all.x=T)
fviz_pca_biplot(pca_nerr, geom='point',
col.var = "#2E9FDF", # Variables color
col.ind = "#696969" # Individuals color
)+
geom_text(aes(label=nerr_h_comp.stn_ids.mrg$Map.Code),hjust=1.2, vjust = 1.2,col='gray60')+ coord_fixed()
nerr_h_comp.stn_ids.pc.mrg<-cbind(nerr_h_comp.stn_ids.mrg,pca_nerr$x)
write.csv(nerr_h_comp.stn_ids.pc.mrg,'dataout/stn_med_pc_spc.csv')pca_nerr_transform = as.data.frame(pca_nerr$x[,1:3])How many clusters?
k.max <- 15 # we want to look at the within squares for clusters 2-15.
wss <- sapply(1:k.max, function(k){kmeans(pca_nerr_transform, k, nstart = 50)$tot.withinss})
plot(1:k.max, wss, type = "b", pch = 19, frame = FALSE, #type = b indicates points joined by lines
xlab = "Number of CLusters K", #pch is the shape of the point, 19 = circle
ylab = "Total Within Clusters Sum of Squares")
fviz_nbclust(pca_nerr_transform, kmeans, method = 'wss')
fviz_nbclust(pca_nerr_transform, kmeans, method = 'silhouette')
#fviz_nbclust(pca_nerr_transform, kmeans, method = 'gap_stat')Although unsupervised metrics such as silhouette width suggested setting the K number of clusters for this dataset to three, four clusters were selected to capture a fourth, generally eutrophic cluster characterized by higher phosphate than the other eutrophic cluster that was generally characterized by high nitrate + nitrite.
v<-c(1:3)
pc.pair<-combn(v, 2)
n_k<-4 # set 4 clusters
for (k in n_k){ #change to range if want to look at multiple clusters
set.seed(42)
kmeans_nerr = kmeans(pca_nerr_transform, centers = k, nstart = 50)
pc.labs<-colnames(kmeans_nerr$centers)
clstr.lab<-LETTERS[1:k]
clusters<-1:k
#clust_clr<-brewer.pal(n = k, name = "Set2")
kmeans_nerr$cluster[kmeans_nerr$cluster == 1]<-6
kmeans_nerr$cluster[kmeans_nerr$cluster == 2]<-5
kmeans_nerr$cluster[kmeans_nerr$cluster == 3]<-8
kmeans_nerr$cluster[kmeans_nerr$cluster == 4]<-7
kmeans_nerr$cluster[kmeans_nerr$cluster == 5]<-1
kmeans_nerr$cluster[kmeans_nerr$cluster == 6]<-3
kmeans_nerr$cluster[kmeans_nerr$cluster == 7]<-2
kmeans_nerr$cluster[kmeans_nerr$cluster == 8]<-4
clust_clr<-c("#66C2A5", "#FC8D62", "#8DA0CB",'#6E260E')
clust_clr
for(c in 1:ncol(pc.pair)){
pair<-v.pair[,c]
xlbl<-paste0('PC',pair[1],' (',round(prop.var[pair[1]]*100,digits=1),'%)')
ylbl<-paste0('PC',pair[2],' (',round(prop.var[pair[2]]*100,digits=1),'%)')
pc.lab<-pc.labs[pair]
p<-fviz_cluster(kmeans_nerr, data = pca_nerr_transform[,pair], geom='point',stand=F, choose.vars=pc.lab,
ggtheme = theme_minimal(), axes = pair) +
geom_label_repel(size =5,aes(label = nerr_h_comp.stn_ids.mrg$Map.Number, colour=cluster),
max.overlaps = Inf,show.legend = F) + coord_fixed() +
scale_colour_manual(values = clust_clr,labels=clstr.lab) +
scale_fill_manual(values = clust_clr,labels=clstr.lab) +
scale_shape_manual(values=c(16,17,15,18),labels=clstr.lab) +
xlab(xlbl) +
ylab(ylbl) +
theme(axis.text=element_text(size=28),
axis.title=element_text(size=32,face="bold"),
legend.title=element_text(size=22),
legend.text=element_text(size=20))
print(p)
}
#
stn_groups<-data.frame(nerr_h_comp$code,kmeans_nerr$cluster)
#join clusters with station metadata
colnames(stn_groups)<-c('code','cluster')
stn_groups2<-merge(stn_groups,nerr_h_comp,by='code')
head(stn_groups2)
unique(stn_groups2$cluster)
stn_groups2$cluster <- factor(stn_groups2$cluster, levels = clusters)
levels(stn_groups2$cluster)<-clstr.lab
for(prm in colnames(nerr_h_comp)[2:ncol(nerr_h_comp)]){
# Basic box plot
p <- ggplot(stn_groups2, aes_string(x='cluster', y=prm, fill='cluster')) +
geom_boxplot(alpha=.6) + scale_fill_manual(values=clust_clr)+ scale_x_discrete("cluster", drop = FALSE) +
theme(axis.text=element_text(size=32),
axis.title=element_text(size=34,face="bold"),
legend.title=element_text(size=24),
legend.text=element_text(size=22))
print(p)
}
data_for_map<-merge(stn_groups2,nerr_h_comp.stn_ids.mrg, on=station)
write.csv(data_for_map,paste0('dataout/data_for_map_spc',k,'clusters_spc.csv'),row.names=F)
data_for_swmp_synth_group<-merge(stn_groups2[,1:2],nerr_h_comp.stn_ids.pc.mrg, on=code)
head(data_for_swmp_synth_group)
data_for_swmp_synth_group
data_for_swmp_synth_group <-data_for_swmp_synth_group %>% dplyr::select("code","cluster","SpCond","Temp",
"DO","pH","Turb","Chla","NH4","NO23","PO4",
"PC1","PC2","PC3","PC4","PC5","PC6","PC7","PC8","PC9")
write.csv(data_for_swmp_synth_group,'dataout/swmp_clstr_med_pc_stations_spc.csv')
}
## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
